Estimation of Near-surface Quality Factors Using Constrained Inversion of Rayleigh-wave Attenuation Coefficients

被引:0
作者
Xia, Jianghai [1 ]
Xu, Yixian [1 ]
Miller, Richard D. [1 ]
Ivanov, Julian [1 ]
机构
[1] China Univ Geosci, Subsurface Imaging & Sensing Lab, Wuhan 430074, Peoples R China
来源
NEAR-SURFACE GEOPHYSICS AND ENVIRONMENT PROTECTION | 2012年
关键词
Rayleigh wave; attenuation coefficient; quality factor; constrained inversion;
D O I
暂无
中图分类号
P5 [地质学];
学科分类号
0709 ; 081803 ;
摘要
Quality factors (Q) of near-surface materials are as important as velocities of the materials in many applications. Only phase information of surface-wave data is utilized when high-frequency (>= 2 Hz) surface-wave data are routinely inverted to determine near-surface shear-wave velocities. Amplitude information of high-frequency surface-wave data can be used to determine quality factors of near-surface materials. Amplitude of seismic data is an exponential function of attenuation coefficients. When calculating attenuation coefficients from changes in amplitude, this nonlinear nature would result in that small variations in amplitude cause huge changes in attenuation coefficients. This result suggests data (attenuation coefficients) normally possess large errors could eventually transfer to a model (quality factors); therefore, constraints (or a priori information) on models are necessary. Because an inversion system to solve this problem is unstable, a regularization parameter must be introduced into an inversion algorithm to stabilize the inversion. These characteristics of the inversion problem allow us to solve the problem as a constrained and regularized linear system. Usually, a set of models that meet the defined constraints can be obtained by solving the system. Based on the linear nature of the inversion system, a smooth model can be selected from the set of models as a solution of the inversion using the L-curve method. A real-world example demonstrates the importance of constraints in finding acceptable realistic quality factors from empirical data.
引用
收藏
页码:176 / 181
页数:6
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